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DOE OSTI2020

Summary of Expansions and Updates in GREET® 2020

The GREET® (Greenhouse gases, Regulated Emissions, and Energy use in Technologies) model has been developed by Argonne National Laboratory with the support of the U.S. Department of Energy (DOE). GREET is a life-cycle analysis (LCA) tool, structured to systematically examine the energy and environmental effects of a wide variety of transportation fuels and vehicle technologies in major transportation sectors (i.e., road, air, marine, and rail) and other end-use sectors, and energy systems. Argonne has expanded and updated the model in various sectors in GREET 2020, and this report provides a summary of the release.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

A Multistage Stochastic Transmission Expansion Algorithm for Wide-Area Planning under Uncertainty

The overall objective for this project was to develop and demonstrate a set of methods for solving the transmission investment problem for a large network considering many possible scenarios of future conditions and multiple decision points when investments can be made. Project sub-objectives achieved this goal through a succession of extending the methods to apply to problems with increasing complexity or additional features, including the number of decision points, whether generation and transmission are co-optimized, and whether AC or DC power flow is used. A transmission model was developed for the Western Electric Coordinating Council (WECC) region, the high-voltage transmission system that serves the western third of the continental U.S. Using a dataset provided by WECC and by researchers from John Hopkins University, we have validated and demonstrated the model and used it to compare the new method for solving multi-stage stochastic transmission planning to several state-of-the-art techniques. The project has resulted in several key outcomes and achievements: The covariance-based method for choosing a small set of hours to represent short-term variability has superior performance in terms of accuracy to existing methods, including K-means clustering and Importance Sampling; The combined partitioning method for long-term uncertainty with the nested clustering approach for choosing representative hours for each long-term group has superior accuracy for equivalent computational effort compared with existing methods; Using the partitioning/clustering method combined with Sample Average Approximation provides both statistical bounds on the quality of the solution and at the same time, a complete investment plan for all contingencies in the full uncertainty set; no existing methods can provide both at the same time; The method is demonstrated to work well for choosing both transmission and generation investments; A variant on the method allows for both scenario selection and simultaneous correction for the error from the DC power flow approximation to provide a tractable method for AC power flow-based transmission planning under uncertainty; The method applied to the WECC case study demonstrates the additional value to the system operator and the consumer of identifying flexible investment options in the near-term decisions. In particular, the case study exhibits significant option value in postponing some transmission additions that appear useful but in some long-term system states create new congestion problems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Net Metering Expansion on the Winnebago Tribe of Nebraska Reservation (Final Technical Report)

The Winnebago Tribe of Nebraska, through their affiliated economic development entity Ho-Chunk, Inc; their affiliated non-profit Ho-Chunk Community Development Corporation; and an additional project partner Nebraska Renewable Energy Systems conducted a community scale renewable energy project on their reservation in Nebraska. Over the two-year project period, we installed PV Solar systems on ten tribally owned commercial/retail/office facilities, which included both six roof mounted and four pole mount installations. The project was undertaken as a part of the Tribe’s broader initiative to increase renewable energy production on the reservation, reduce the Tribe’s financial obligations for purchasing energy, and lessen our reliance upon outside sources of energy to meet our basic needs. The project enabled us to formalize and strengthen community collaborations and build our capacity to pursue additional renewable energy opportunities that will enhance our energy sovereignty.

14 SOLAR ENERGY↗
DOE OSTI2020

Building Assessment of Radon Reduction Interventions with Energy Retrofits Expansion (The BEX Study): Final Report

This report presents the findings from a study that was performed to assess whether current precautionary measures used by the US Department of Energy Weatherization Assistance Program (WAP) are effective for preventing indoor radon increases following weatherization. The study results show that current practices have produced substantial benefit compared to previous practices, and that there are no statistically significant changes in indoor radon levels on the lowest living levels with these practices following weatherization.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2021

Solar Photovoltaic (PV) Manufacturing Expansions in the United States, 2017-2019: Motives, Challenges, Opportunities, and Policy Context

This report analyzes U.S. PV manufacturing announcements from 2017 through July-2019 and explores the potential impact of tariffs on the competitiveness of U.S. PV module manufacturing. First, the fraction of announcements that resulted in established facilities in the time frame specified is analyzed, as well as firm nationality and the existence of any other U.S. facilities for the firm. The prevalence of different PV product types among the announcements was also analyzed, as well as the type of facilities selected for development (greenfield, existing PV factories, or repurposed buildings). The cost to build these facilities was also analyzed in the context of their capacity, the value of incentives received by state and local governments, and the number of jobs created. Case studies of Auxin Solar, First Solar, Hanwha Q Cells, JinkoSolar, LG, Silfab, Solaria, and SunPower were conducted and highlight five factors influencing firms’ decisions to expand their U.S. PV production capacity. These included: 1) proximity to demand, including supply contracts and demand for domestic content 2) tariffs and other incentives. The Section 201 tariffs on PV module imports were often described helpful but tariffs on cell imports (Section 201) or materials (Section 301, Section 232) were often described as counterproductive since U.S. supply chains do not exist for many necessary goods. The corporate tax decrease and local incentives were often mentioned as helpful. 3) the ability to move quickly in order to maximize the benefit of the Section 201 tariffs. This affected decisions to select localities with faster permitting or moving into existing buildings. 4) competition with scale, where competing with Asian PV imports or avoiding imports of material from China was challenging due to the larger scale of Asian manufacturers. Additionally, smaller firms expressed concerns that larger firms may not need their U.S. facilities to profitable. 5) access to capital, which was a particular challenge for smaller firms. Several U.S. tariffs affect the economics of PV cells, modules, and balance-of-module (BOM) materials, some of which are applicable to a long list of countries and others applicable only to China or Taiwan. We analyze how the tariffs interact to affect the prices of c-Si modules sourced under various assumptions about domestic and imported components and assembly. We estimate module prices under a range of baseline scenarios featuring U.S.-assembled modules with Southeast Asian cells (not from China or Taiwan). When all BOM components are sourced from the United States, baseline module prices are $0.37/W (below the 2.5-GW Section 201 cell cap) to $0.42/W (above the 2.5-GW cell cap). If all BOM components are sourced from China, the module price in this baseline U.S.-assembly scenario can reach up to $0.60/W. Imported module prices are lower than or within the range of the U.S.-assembled baseline prices under some conditions. Importing bifacial modules from Southeast Asia is the lowest-priced alternative, at $0.35/W, because bifacial modules are excluded from the Section 201 tariffs. Importing Southeast Asia modules that contain U.S. cells results in a price of $0.38/W, also owing to a Section 201 exclusion. Importing Southeast Asian modules that have Southeast Asian cells yields a price of $0.44/W, and importing Chinese modules that have U.S. cells yields a price of $0.58/W. These results suggest that U.S. tariff policy in 2019 may encourage U.S. assembly of mono-facial c-Si modules if the 2.5-GW cell import cap is not reached and Chinese BOM imports are negligible. However, some imported module options may offer the lowest prices if the 2.5-GW cell import cap is reached and/or U.S. module manufacturers must rely on significant Chinese BOM content. The analysis shows the 2.5-GW cell cap may be exceeded in 2019 and following years. It is also likely that U.S. module manufacturers will need to use at least some Chinese BOM content, since U.S. module manufacturers have stated that U.S. supply chains do not exist (or do not exist at a sufficient scale) for most BOM components, which makes them at least partially reliant on Chinese BOM and thus subject to Section 301 tariffs.

14 SOLAR ENERGY↗
DOE OSTI2021

Expansion of Machine-Learning Method for Classifying Neutron Resonances

The understanding of astrophysics processes and the performance of nuclear reactors and other nuclear systems depend on a precise description of the neutron interaction cross sections for materials and nuclei present in these environments. At low neutron energies, these cross sections exhibit resonance structure represented by sharp enhancements when the neutron energy is sufficiently close to excited levels in a compound nucleus. Such resonances can be characterized by their quantum numbers relative to angular momenta, which are often deduced in an ad hoc and irreproducible manner from the shape of the cross sections. The correct assignment of the quantum numbers of neutron resonances is therefore of paramount importance. To address this we have developed a machine-learning method to automate the identification and correction of these spin assignments. The algorithm is trained from simulated data, generated from statistical properties of resonance data for a given nucleus, to mimic the errors found in real data. In this project we describe five independent approaches to further develop and expand the applicability of the machine-learning spin classifier: i) Feature impact; ii) Integration with the Atlas; iii) Training optimization; iv) Spacings systematics; and v) Validation with polarized data. The premises, methods, results, and future perspectives are discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Summary of Expansions and Updates in GREET ® 2021

The GREET® (Greenhouse gases, Regulated Emissions, and Energy use in Technologies) model has been developed by Argonne National Laboratory (Argonne) with the support of the U.S. Department of Energy (DOE). GREET is a life-cycle analysis (LCA) tool, structured to systematically examine the energy and environmental effects of a wide variety of transportation fuels and vehicle technologies in major transportation sectors (i.e., road, air, marine, and rail) and other end-use sectors, and energy systems. Within the transportation sector, GREET covers road, air, water, and rail transportation sub-sectors. Recently, GREET was expanded to cover the building sector. Historically, GREET includes LCA of various materials such as steel, aluminum, cement, and different plastic types. Argonne has expanded and updated the model in various sectors in GREET 2021, and this report provides a summary of the release.

09 BIOMASS FUELS↗
DOE OSTI2021

Providencia Island High-Level Power System Capacity Expansion Analyses [Slides]

Results of a high level cost-benefit analysis using HOMER Pro software are presented for Providencia Island, Colombia. The analysis focuses on integrating solar photovoltaics (PV) and a battery energy storage system (BESS) into an existing diesel-only remote power system. The analysis uses fuel costs and discount rates provided by the stakeholders and NREL-derived capital cost estimates.

14 SOLAR ENERGY↗
DOE OSTI2022

Closed-Loop Pumped Storage Hydropower Resource Assessment for the United States. Final Report on HydroWIRES Project D1: Improving Hydropower and PSH Representations in Capacity Expansion Models

Pumped storage hydropower represents the bulk of the United States' current energy storage capacity: 23 gigawatts (GW) of the 24-GW national total (Denholm et al. 2021). This capacity was largely built between 1960 and 1990. PSH is a mature and proven method of energy storage with competitive round-trip efficiency and long life spans. These qualities make PSH a very attractive potential solution to energy storage needs, particularly for longer-duration storage (8 hours or more); such storage will be crucial to bridge gaps in electricity production as variable wind and solar production continue to comprise an ever-larger portion of the United States' energy portfolio (Cole et al. 2021; Frazier et al. 2021). However, it is unclear how much potential the United States has for the development of new PSH. No new large PSH has been constructed in the United States since the 1990s, and attempts to quantify technical potential capacity from PSH project applications to the Federal Energy Regulatory Commission (FERC) suffer from inconsistent site and cost evaluation methodologies and likely are not representative of all PSH opportunities. This study seeks to better under understand the technical potential for PSH development in the United States by developing a national-scale resource assessment for closed-loop PSH. Individual sites are not modeled in sufficient detail for project-level development, but they do provide valuable insights into potential resource areas across the United States, including the ability to provide estimates for a range of long-term development scenarios.

13 HYDRO ENERGY↗